HUNTS: A trajectory recommendation system for effective and efficient hunting of taxi passengers

Ye Ding, Siyuan Liu, Jiansu Pu, Lionel M. Ni

Research output: Contribution to journalConference article

31 Scopus citations

Abstract

Nowadays, there are many taxis traversing around the city searching for available passengers, but their hunts of passengers are not always efficient. To the dynamics of traffic and biased passenger distributions, current offline recommendations based on place of interests may not work well. In this paper, we define a new problem, global-optimal trajectory retrieving (GOTR), as finding a connected trajectory of high profit and high probability to pick up a passenger within a given time period in real-time. To tackle this challenging problem, we present a system, called HUNTS, based on the knowledge from both historical and online GPS data and business data. To achieve above objectives, first, we propose a dynamic scoring system to evaluate each road segment in different time periods by considering both picking-up rate and profit factors. Second, we introduce a novel method, called trajectory sewing, based on a heuristic method and the Skyline technique, to produce an approximate optimal trajectory in real-time. Our method produces a connected trajectory rather than several place of interests to avoid frequent next-hop queries. Third, to avoid congestion and other real-time traffic situations, we update the score of each road segment constantly via an online handler. Finally, we validate our system using a large-scale data of around 15, 000 taxis in a large city in China, and compare the results with regular taxis' hunts and the state-of-the-art.

Original languageEnglish (US)
Article number6569127
Pages (from-to)107-116
Number of pages10
JournalProceedings - IEEE International Conference on Mobile Data Management
Volume1
DOIs
StatePublished - Sep 11 2013
Event14th International Conference on Mobile Data Management, MDM 2013 - Milan, Italy
Duration: Jun 3 2013Jun 6 2013

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

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